
This paper describes a low-complexity, highefficiency, lossy-to-lossless 3D image coding system. The proposed system is based on a novel probability model for the symbols that are emitted by bitplane coding engines. This probability model uses partially reconstructed coefficients from previous components together with a mathematical framework that captures the statistical behavior of the image. An important aspect of this mathematical framework is its generality, which makes the proposed scheme suitable for different types of 3D images. The main advantages of the proposed scheme are competitive coding performance, low computational load, very low memory requirements, straightforward implementation, and simple adaptation to most sensors.
Bitplane image coding, bitplane image coding, 3D image coding, Entropy coding, JPEG2000, Computing methodologies for image processing, Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science), entropy coding
Bitplane image coding, bitplane image coding, 3D image coding, Entropy coding, JPEG2000, Computing methodologies for image processing, Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science), entropy coding
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